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methods with a particular focus on deep learning and image analysis. The project relies on a close collaboration with researchers at the Department of Immunology, Genetics and Pathology (IGP) at Uppsala
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of students. A limited amount of teaching may be included (max 20%). Requirements PhD degree in machine learning, computer science, scientific computing, mathematics, statistics or a related field
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taking part in the supervision of students. A limited amount of teaching may be included (max 20%). Requirements PhD degree in machine learning, scientific computing, statistics, physics or a related
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Python and/or R. Experience in deep learning, machine learning, or large-scale omics data analysis. A high level of self-motivation and independence, good problem-solving skills, and the ability to
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requirement. Knowledge of statistics, AI/ML, mathematical modeling is highly desirable. Knowledge of AML and treatment resistance as well as single-cell deep learning frameworks such as scVI are desirable
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reproducible code by using code sharing platforms, version control, workflow languages and container solutions is a merit. Experience in training deep learning-based models on HPC-resources is also meriting. A